Streaming-based pricing helps. Local processing removes the bill entirely.
Coralogix's streaming architecture and TCO-based pricing is a real improvement over legacy per-GB vendors, routing data into cheaper tiers instead of billing everything at one flat rate. It's still volume-based, though, and telemetry still passes through Coralogix's platform to get there. Randoli removes the volume axis entirely and processes locally.
Where it actually differs
Ingestion pricing
$0 ingestion. No volume axis at all, regardless of tier. Telemetry is processed locally in your cluster, full stop.
The TCO Optimizer routes data into tiered pipelines (Frequent Search, Monitoring, Compliance, Archive/Blocked) by intent, genuinely smarter than flat per-GB billing. It's still priced on volume; more data still costs more, just tiered instead of flat.
Data location
Raw logs and traces never leave your cluster. Processing happens where the data is generated, not after it's shipped somewhere else.
Telemetry streams through Coralogix's platform for processing and routing. Some plans support landing storage in a customer-owned S3 or GCS bucket, a genuine sovereignty feature, but analysis still runs in Coralogix's environment first.
Retention
Retention runs on your own infrastructure. One rate, no separate retention tier to negotiate against.
Retention and query performance depend on which tier data was routed into at ingest time, a decision made upfront, per log stream.
Kubernetes cost attribution
Cost attribution by workload and team is native to the platform, on the same pipeline as logs, traces, and metrics.
Not a core focus of the platform. Coralogix is built for log and metric analytics, not Kubernetes cost or chargeback reporting.
AI incident response
Raiya correlates signals across logs, traces, and metrics, proposes root cause with supporting evidence, and executes approved runbooks.
Some AI-assisted flow and anomaly detection features exist, but no full runbook-executing incident response agent comparable to Raiya.
The numbers
Volume assumption: ~300 GB logs/day and ~50 M trace spans/day per 100 hosts. Coralogix estimates based on published TCO Optimizer / streaming pricing at standard tiers. Randoli at $0.04/host/hour.
| Scenario | Coralogix (est.) | Randoli |
|---|---|---|
| ~$2,000/mo | ~$1,440/mo | |
Randoli: $0.04/host/hr × 50 hosts × ~730 hrs/mo ≈ ~$1,440/mo Coralogix (est.): illustrative, based on that vendor's published rate card at the volume in this scenario — see the assumption note above. | ||
| ~$7,800/mo | ~$5,760/mo | |
Randoli: $0.04/host/hr × 200 hosts × ~730 hrs/mo ≈ ~$5,760/mo Coralogix (est.): illustrative, based on that vendor's published rate card at the volume in this scenario — see the assumption note above. | ||
| ~$19,000+/mo | ~$14,400/mo (volume discounts available) | |
Randoli: $0.04/host/hr × 500 hosts × ~730 hrs/mo ≈ ~$14,400/mo Coralogix (est.): illustrative, based on that vendor's published rate card at the volume in this scenario — see the assumption note above. | ||
Illustrative estimates based on published rate cards and typical usage patterns, not a quote. Confirm current numbers before publishing.
Why teams switch
Coralogix earns real credit here. The TCO Optimizer's tiered routing is a genuinely smarter way to charge for telemetry than flat per-GB billing, DataPrime is a capable query language once a team climbs the learning curve, and the option to land storage in a customer-owned bucket is a real sovereignty feature most usage-based vendors don't offer.
Teams that switch are usually the ones who've concluded that a smarter volume-based bill is still a volume-based bill, and that data streaming through a vendor's platform for processing is still data leaving the environment, even if it lands back in a bucket they own. Randoli removes the volume axis and the processing step both, at a flat rate per host.